The exemplary embodiment relates to digital image processing. It finds particular application in connection with the automated harmonization of a set of images in which the harmonization process is specific to a content-based category assigned to the images in the set.
The creation of multimodal documents which include multiple images, often arranged in close proximity to one another, typically involves a number of processing steps, including resizing of images, cropping of relevant parts, image enhancement, and the like as well as complementing the images with appropriate choices of text features, such as font, size and color, and overall layout of the document. When images are arranged in close proximity to one another, either on the same page or on closely adjacent pages of the same document, differences in the images are emphasized and may detract from the overall aesthetic impact of the document. For example, a graphic designer of a newsletter may wish to include an arrangement of portraits of several people for a company newsletter. The portraits may have been obtained at different times under different lighting conditions and against different backgrounds. The graphic designer may apply manual touch-up operations to make the images look more homogeneous, such as manually identifying the background region and recoloring it, making faces of approximately the same dimensions, and adjusting overall image characteristics, such as color balance, sharpness, white balance, resolution, color noise, brightness, contrast, luminosity, removing digital artifacts and analog artifacts, and the like. However, these harmonization operations are time consuming and often impractical unless high document quality is a requirement.
There remains a need for an automated or semi-automated method of image harmonization for applications such as those mentioned above.